Markov: Maths for the Newspaper Reader

September 14, 2017

Remarkable. I read a pretty good write up called “That’s Maths: Andrey Markov’s Brilliant Ideas Are Still Bearing Fruit.” I noted the source of the article: The Irish Times. A “real” newspaper. Plus it’s Irish. Quick name a great Irish mathematician? I like Sir William Rowan Hamilton, who my slightly addled mathy relative Vladimir Igorevich Arnold and his boss/mentor/leader of semi clothed hikes in the winter Andrey Kolmogorov thought was an okay guy.

Markov liked literature. Well, more precisely, he liked to count letter frequencies and occurrence in Russian novels like everyone’s fave Eugene Onegin. His observations fed his insight that a Markov Process or Markov Chain was a useful way to analyze probabilities in certain types of data. Applications range from making IBM Watson great again to helping outfits like Sixgill generate useful outputs. (Not familiar with Sixgill? I cover the company in my forthcoming lecture at the TechnoSecurity & Digital Forensics Conference next week.)

I noted this passage which I thought was sort of accurate or at least close enough for readers of “real” newspapers:

For a Markov process, only the current state determines the next state; the history of the system has no impact. For that reason we describe a Markov process as memoryless. What happens next is determined completely by the current state and the transition probabilities. In a Markov process we can predict future changes once we know the current state.

The write up does not point out that the Markov Process becomes even more useful when applied to Bayesian methods enriched with some LaPlacian procedures. Now stir in the nuclear industry’s number one with a bullet Monte Carlo method and stir the ingredients. In my experience and that of my dear but departed relative, one can do a better job at predicting what’s next than a bookie at the Churchill Downs Racetrack. MBAs on Wall Street have other methods for predicting the future; namely, chatter at the NYAC or some interactions with folks in the know about an important financial jet blast before ignition.

A happy quack to the Irish Times for running a useful write up. My great uncle would emit a grunt, which is as close as he came to saying, “Good job.”

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Stephen E. Arnold monitors search, content processing, text mining
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